基于提升Directionlet变换的零块嵌入图像编码算法

提出一种新的基于提升Directionlet变换的图像压缩算法, 能有效捕捉图像中的多方向各向异性特征, 并具备格形可分离的滤波和采样结构. 利用四叉树分块寻找局部最优的变换方向, 针对Directionlet变换系数分布构造了块集合分裂嵌入编码, 并通过改进链表排序方式和设计新的上下文算术编码器, 进一步提高压缩性能. 仿真实验结果表明, 与基于原始Directionlet变换的压缩算法和基于小波变换的SPECK, SPIHT, JPEG 2000等经典算法相比, 本文算法在性能参数和视觉效果方面均有较大提高, 且在低比特率下仍能较完整地保留图像中的边缘和细节信息.

Zeroblock Embedded Image Coding Algorithm Based on Lifting Directionlet Transform

A new image compression algorithm based on lifting directionlet transform (LDT) is proposed. This transform captures the multi-directional anisotropic image features efficiently and processes the structure of lattice-based separable filtering and sampling. The quad-tree segmentation is designed for direction optimization of local region, and a set-partitioned embedded block algorithm for the statistic distribution property of transform coefficients is adopted. The coding performance is improved by designing the new chained list sorting and context-based arithmetic coder. The experimental results show that our proposed compression algorithm outperforms the standard wavelet-based SPECK, SPIHT, JPEG,2000 and original directionlet-based methods both in terms of peak signal to noise ratio (PSNR) and visual quality. Especially at the low-rate, our algorithm can preserve better the detailed information.